Senior Software Engineer

Who you are

• We do not require a background in robotics
• We're looking for engineers who are self driven, optimistic, creative, and resourceful
• We have no requirements for a background in robotics, but find most success with engineers excited by the domain and looking to apply their expertise and experience in a new area
• Our ideal candidate will be open to doing approximately 70% back-end and 30% front-end work with flexibility to sway more towards one or the other, depending on current projects and team needs
• This is a generalist role first — but on the AI team, so we're looking for someone whose breadth already reaches into at least one AI-adjacent domain
• Experience: You have a strong technical background, including 5-10 years of experience working in complex environments
• AI-adjacent depth (strongly preferred): You have professional experience in at least one of ML Ops, data pipelines, or computer vision — for example building training or inference infrastructure, running large-scale data ingestion and curation, or shipping a vision pipeline to production. You don't need to have trained the models yourself
• Growth + Optimism: You are excited by new domains and challenges, and eager to pick up new context to accelerate your impact
• Clarity of Communication: You excel in written and verbal communication and enjoy leveraging your skills to support your peers
• Impact Driven: You relentlessly seek user impact and value execution over technical idealism
• Proactive Simplicity: You prioritize simplicity, reliability, and velocity and proactively identify opportunities to improve proposed implementations or incumbent systems
• Excelling in Ambitious Environments: You excel in dynamic and ambitious environments, working with a diverse group of individuals and backgrounds

What the job involves

• We're looking for a seasoned, broad software engineer to join our AI team and build the systems our models depend on. Our AI researchers push the modeling frontier; this role owns nearly everything around it — the data that goes in, the infrastructure that trains and evaluates, the perception plumbing that connects cameras to the robot, and the product surfaces that put all of it in a customer's hands
• The AI team is small, so the surface area is wide and the ownership is real. You may move between adding functionality to the data ingestion pipeline, a camera calibration bug, and a customer-facing feature in the same month — and you'll decide which of those matters most this week
• Projects across the AI team's stack
• Ship the product surfaces that expose AI capabilities to users — the applications and APIs customers actually touch
• Mentor and advise other engineers as well as peers on technical and personal advancement
• Drive technical decision making and implementation through hands-on and technically deep work
• Plus ownership of one or more of these, depending on where your experience is strongest:
• Data pipelines: the flywheel for end-to-end AI — ingestion of teleop and demonstration data, labeling and curation tooling, dataset quality metrics
• Training and evaluation infrastructure: training pipelines, experiment tracking, GPU orchestration, model versioning, and deployment out to robots
• Perception integration: camera calibration, vision pipelines, and getting model outputs into the robot runtime reliably

Benefits

• Employee stock options
• Paid time off
• Medical/dental/vision insurance
• Life insurance & disability insurance
• 401(k)